Function of 2 variables, max/min test, D=0 and linear dependence

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Discussion Overview

The discussion revolves around the conditions for determining maxima, minima, and saddle points of functions of two variables using the discriminant \(D\). Participants explore the implications of \(D=0\) and the linear dependence of first partial derivatives, as well as the characteristics of functions whose partials exhibit linear dependence.

Discussion Character

  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • Some participants clarify that the statement regarding \(D=0\) refers to the linear dependence of the first partial derivatives \(f_x\) and \(f_y\), not the linear dependence of the variables \(x\) and \(y\).
  • There is a discussion about the characteristics of functions whose partial derivatives are linearly dependent, with some suggesting that such functions may be constant multiples of each other.
  • One participant proposes that for a function \(f(x,y)\) to have linearly dependent partials, all terms must be multiples of \((xy)^n\) or contain terms of \(x\) or \(y\) with powers at most 2.
  • Another participant expresses a need for an example of a function where both \(f_x\) and \(f_y\) equal zero and \(D=0\).
  • A later reply provides an example function and discusses its Hessian matrix, noting that it has a determinant of zero, which aligns with the discussion on linear dependence.

Areas of Agreement / Disagreement

Participants generally agree on the interpretation of linear dependence in the context of partial derivatives, but there is no consensus on the specific characteristics of functions that lead to this condition or the implications of \(D=0\).

Contextual Notes

Some participants mention the need for knowledge of linear algebra concepts, such as the Hessian and quadratic forms, to better understand the implications of the discussion.

binbagsss
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##f(x,y)##

a critical point is given by ##f_x=0## and ##f_y=0## simultaneously.

the test is:

##D=f_{xx}f_{yy}-(f_{xy})^2 ##

if ##D >0 ## and ##f_{xx} <0 ## it is a max
if ##D >0 ## and ##f_{xx} >0 ## it is a min
##D >0 ## is is a saddle
if ##D =0 ## it is inconclusive, and ##f_x## and ##f_y## are not linear independent.

I'm stuck on the ##D=0## comment re linear independence. So is this saying that ##x## and ##y## are not linear indepedent?

So if i take an arbitary function ##f(x,y) ## and ##y=h(x)##, h some linear function, then I should get ##D=0## or not?
 
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It is saying that the two first partials are linearly dependent, not that x and y are linearly dependent.
 
Mark44 said:
It is saying that the two first partials are linearly dependent, not that x and y are linearly dependent.

What is characteristic of a function whose partials are linearly dependent?
 
binbagsss said:
What is characteristic of a function whose partials are linearly dependent?
If two functions (partials in this case) are linearly dependent, then each will be a constant multiple of the other.
 
Mark44 said:
If two functions (partials in this case) are linearly dependent, then each will be a constant multiple of the other.
yup, so if i have a ##f(x,y)## function all term must be a multiple of ##(xy)^n## , ##n \in R## or if it contains terms solely of ##x## or ##y## they must be of at most the power of ##2##? (To conclude the partials ##f_x## and ##f_y## are linear dependent, not higher partials)?

edit: re second comment is incorrect, but would yield ##D=0## without implying that ##f_x## and ##f_y## are linearly independent? so in OP comment only holds for higher powers? or a function without sole terrms of x or y if the power is lower
 
binbagsss said:
yup, so if i have a ##f(x,y)## function all term must be a multiple of ##(xy)^n## , ##n \in R## or if it contains terms solely of ##x## or ##y## they must be of at most the power of ##2##? (To conclude the partials ##f_x## and ##f_y## are linear dependent, not higher partials)?
I haven't worked out an example. You want a function f(x, y) such that fx = fy = 0, and for which the discriminant D = 0.
 
Mark44 said:
I haven't worked out an example. You want a function f(x, y) such that fx = fy = 0, and for which the discriminant D = 0.
apologies edited post since above
 
binbagsss said:
##f(x,y)##

a critical point is given by...
##D >0 ## is is a saddle

this is a typo and should say less than zero.
binbagsss said:
if ##D =0 ## it is inconclusive, and ##f_x## and ##f_y## are not linear independent.

I'm stuck on the ##D=0## comment re linear independence. So is this saying that ##x## and ##y## are not linear indepedent?

This is a lot easier in my view if you know bits about linear algebra. Do you know what a Hessian is? How about a quadratic form?

consider the 2 variable function (I used ##x_1, x_2## instead of ##x,y##:

edit: (due to some domain subtleties, the below is a better example than the prior function I mentioned)

##f(x_1,x_2) = (x_1 + x_2)^2 = x_1^2 + x_2^2 + 2x_1 x_2##

The Hessian is given by
##
\mathbf H = \begin{bmatrix}
2 & 2\\
2 & 2
\end{bmatrix} = 2 \big(\mathbf 1 \mathbf 1^T\big)##

This is a rank one matrix and hence has determinant of zero. (Equivalently compute the determinant directly and see ##2*2 - 2*2 = 0## )
 
Last edited:

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